Paper Citation Record · LEDGER

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA

As of 18 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 2 inbound Pith citation observations for arXiv:2506.21569.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.21569 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:18:23.565342Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T18:43:44.967410Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-15T14:35:55.969560Z

Reference resolution

30 of 30 outbound references displayed

verified exact0
verified fuzzy27
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cb0b3b83-562a-484a-b50e-a456bb9c33e1 · outbound

This paper cites A survey on assertion-based hardware verification,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA A survey on assertion-based hardware verification,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:30.654817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3320e52a-168e-433c-b75d-dd9108b9f2b4 · outbound

This paper cites Ieee standard for systemverilog–unified hardware design, specification, and verification language,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA Ieee standard for systemverilog–unified hardware design, specification, and verification language,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:30.387600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 81109ff6-0ab0-4271-9bde-c9e50250316c · outbound

This paper cites GoldMine: automatic assertion generation using data mining and static analysis,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA GoldMine: automatic assertion generation using data mining and static analysis,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:30.066808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cdf107fe-ffeb-4e85-a030-b32ea0f45ae8 · outbound

This paper cites Automated generation of security assertions for rtl models,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA Automated generation of security assertions for rtl models,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:29.795528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 89cc5c0d-382d-4618-8d60-fadddae35940 · outbound

This paper cites Generative AI assertions in UVM-based system verilog functional verification,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA Generative AI assertions in UVM-based system verilog functional verification,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:29.576808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cd60ef33-1919-4a38-a678-402d2774de6b · outbound

This paper cites ChI- RAAG: ChatGPT informed rapid and automated assertion generation,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA ChI- RAAG: ChatGPT informed rapid and automated assertion generation,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:29.315549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 33217cc6-5de5-4524-9ea6-4737b1f58a2b · outbound

This paper cites AssertLLM: Generating hardware verification assertions from design specifications via multi-llms,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA AssertLLM: Generating hardware verification assertions from design specifications via multi-llms,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:29.023843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 579a0e39-871f-49c5-9d00-ea9b1079926a · outbound

This paper cites SpecToSV A: Circuit specification document to systemverilog assertion translation,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA SpecToSV A: Circuit specification document to systemverilog assertion translation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:28.700852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 06dd57d3-a365-4749-9747-89d0c8b65b4d · outbound

This paper cites NSPG: Natural language processing-based security property generator for hardware security assurance,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA NSPG: Natural language processing-based security property generator for hardware security assurance,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:28.346619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bde372da-738d-49c3-9c13-6e27cdcab49f · outbound

This paper cites GLAsT: Learning formal grammars to translate natural language specifications into hardware assertions,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA GLAsT: Learning formal grammars to translate natural language specifications into hardware assertions,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:27.971205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8fc9fc52-8216-41a5-8cbb-fb0a8552f9f8 · outbound

This paper cites EASE: Enabling hardware assertion synthesis from english,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA EASE: Enabling hardware assertion synthesis from english,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:27.607898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 78fd0795-db8f-4018-94fc-daa6be118e03 · outbound

This paper cites nl2spec: Interactively translating unstructured natural language to temporal logics withlarge language models,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA nl2spec: Interactively translating unstructured natural language to temporal logics withlarge language models,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:27.261120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3dd9905c-b25c-49dc-84da-6f4a7e0b705f · outbound

This paper cites Spec2Assertion: Automatic Pre-RTL Assertion Generation using Large Language Models with Progressive Regularization.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA Spec2Assertion: Automatic Pre-RTL Assertion Generation using Large Language Models with Progressive Regularization

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T04:18:21.361536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39afbfe7-3f8e-4cd0-b315-75b763c01aef · outbound

This paper cites Automatic high-quality verilog assertion generation through subtask-focused fine- tuned LLMs and iterative prompting,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA Automatic high-quality verilog assertion generation through subtask-focused fine- tuned LLMs and iterative prompting,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:27.089560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 33a4cc80-b5e4-44ea-8044-f99210432b62 · outbound

This paper cites Ieee standard for systemverilog–unified hardware design, specification, and verification language,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA Ieee standard for systemverilog–unified hardware design, specification, and verification language,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:26.841763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b29eec5d-3e44-4157-b0d3-9e1a4bed7fec · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive NLP tasks,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA Retrieval-augmented generation for knowledge-intensive NLP tasks,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:26.585216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0e05916f-51f1-4ce5-afcf-ac940e3f1966 · outbound

This paper cites LLM-based and retrieval-augmented control code generation,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA LLM-based and retrieval-augmented control code generation,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:26.437490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e9875207-0e94-4fd6-9483-f4f69c9ef777 · outbound

This paper cites Benchmarking retrieval- augmented generation for medicine,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA Benchmarking retrieval- augmented generation for medicine,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:26.163587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6c9d2282-19d6-49c6-b86f-f0aca45e27a7 · outbound

This paper cites Improving retrieval for RAG based question answering models on financial doc- uments,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA Improving retrieval for RAG based question answering models on financial doc- uments,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:25.941706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 127b4a90-f6f2-469c-9674-b8f98316dac4 · outbound

This paper cites Toward con- versational agents with context and time sensitive long-term memory,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA Toward con- versational agents with context and time sensitive long-term memory,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:25.695895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 470d6ad6-ba14-4334-a8a0-650c6fcfa62e · outbound

This paper cites ChunkRAG: Novel LLM-chunk filtering method for rag systems,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA ChunkRAG: Novel LLM-chunk filtering method for rag systems,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:25.483614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1cf56cd8-a5a3-47e4-a39b-36477e9f5935 · outbound

This paper cites MAIN-RAG: Multi-Agent Filtering Retrieval- Augmented Generation,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA MAIN-RAG: Multi-Agent Filtering Retrieval- Augmented Generation,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:25.338728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e6e18005-3255-42cd-a505-33f58c0bc5d2 · outbound

This paper cites Don’t forget to connect! improving rag with graph-based reranking,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA Don’t forget to connect! improving rag with graph-based reranking,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:25.149841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0bf29fca-83b5-4a1a-a6dc-92bb1f3615ef · outbound

This paper cites AssertionBench: A benchmark to evaluate large-language models for assertion generation,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA AssertionBench: A benchmark to evaluate large-language models for assertion generation,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:24.871233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 34a53360-9e81-4a07-888f-5cd4f8be435a · outbound

This paper cites FVEval: Understanding Language Model Capabilities in Formal Verification of Digital Hardware.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA FVEval: Understanding Language Model Capabilities in Formal Verification of Digital Hardware

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T04:18:23.084403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2857f9d5-0dbc-4ff2-8362-7762748d8fb8 · outbound

This paper cites Cadence JasperGold Formal Verification Platform,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA Cadence JasperGold Formal Verification Platform,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:24.666027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 85f2d7db-e139-4a26-a1b9-b842f48ddd58 · outbound

This paper cites Qwen2. 5-coder technical report,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA Qwen2. 5-coder technical report,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:24.273307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8ee770d9-b1cc-4198-a57b-b5da68255280 · outbound

This paper cites Llamafactory: Unified efficient fine-tuning of 100+ language models,.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA Llamafactory: Unified efficient fine-tuning of 100+ language models,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:23.963928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2408487c-f449-45ed-ac09-9d09de146c3b · outbound

This paper cites Available: https://www.cadence.com/.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA Available: https://www.cadence.com/

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:18:24.520115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8e45d05f-405c-4b11-b5b4-0927779ce0b3 · outbound

This paper cites AssertionBench: A Benchmark to Evaluate Large-Language Models for Assertion Generation.

Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA AssertionBench: A Benchmark to Evaluate Large-Language Models for Assertion Generation

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T04:18:22.937013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation d6d9a5ca-f814-48df-bb67-78bf2bc26c26 · inbound

FVRuleLearner: Operator-Level Reasoning Tree (Op-Tree)-Based Rules Learning for Formal Verification cites this paper.

FVRuleLearner: Operator-Level Reasoning Tree (Op-Tree)-Based Rules Learning for Formal Verification Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-15T14:35:55.970990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 00a00dda-f0a3-4653-b762-aac992d13363 · inbound

FVRuleLearner: Operator-Level Reasoning Tree (Op-Tree)-Based Rules Learning for Formal Verification cites this paper.

FVRuleLearner: Operator-Level Reasoning Tree (Op-Tree)-Based Rules Learning for Formal Verification Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-02T18:43:44.967410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.